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dc.contributor.authorYang, Y
dc.contributor.authorHospedales, TM
dc.contributor.authorUAI
dc.date.accessioned2024-07-11T14:56:12Z
dc.date.available2023-07-01
dc.date.available2024-07-11T14:56:12Z
dc.date.issued2023-01-01
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/98037
dc.description.abstractWe present a mixture of normalizing flows (MoNF) approach to European option pricing with guarantees that its estimations are free from static arbitrage. In contrast to many existing methods that meet economic rationality constraints (e.g., non-arbitrage) by introducing auxiliary losses, our solution meets those constraints exactly by design. To achieve this, we propose to build a model for risk neutral density using normalizing flows, which results in a pricing model, instead of modelling the option pricing function directly. First, we convert the constraints for direct pricing models to the constraints for models backed by risk neutral density estimation, then we design a specific NF architecture that meets these constraints. Furthermore, we find that employing a mixture of such normalizing flows improves the performance significantly, compared to using a deeper single NF. Finally, we present a mechanism to regularise the proposed model, and this regularisation can serve as a bridge between our method and any sample-based mathematical finance method. The evaluations on five option datasets show superiority of our method compared to mathematical finance solutions and some other neural networks based methods. The code is available at https://github.com/qmfin/MoNF.en_US
dc.format.extent2390 - 2399
dc.titleMixture of Normalizing Flows for European Option Pricingen_US
dc.typeConference Proceedingen_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
pubs.volume216en_US
dcterms.dateAccepted2023-07-01


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